activity
20222025
most citedRealizing Stabilized Landing for Computation-Limited Reusable Rockets: A Quantum Reinforcement Learning Approach

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2025

Hallucination-Aware Generative Pretrained Transformer for Cooperative Aerial Mobility Control

Hyojun Ahn, Seungcheol Oh, Gyu Seon Kim +3

This paper proposes SafeGPT, a two-tiered framework that integrates generative pretrained transformers (GPTs) with reinforcement learning (RL) for efficient and reliable unmanned a…

eess.SP2024★ 1 cited

Quantum Multi-Agent Reinforcement Learning for Cooperative Mobile Access in Space-Air-Ground Integrated Networks

Gyu Seon Kim, Yeryeong Cho, Jaehyun Chung +4

Achieving global space-air-ground integrated network (SAGIN) access only with CubeSats presents significant challenges such as the access sustainability limitations in specific reg…

cs.AI2023★ 1 cited

Realizing Stabilized Landing for Computation-Limited Reusable Rockets: A Quantum Reinforcement Learning Approach

Gyu Seon Kim, JaeHyun Chung, Soohyun Park

The advent of reusable rockets has heralded a new era in space exploration, reducing the costs of launching satellites by a significant factor. Traditional rockets were disposable,…

cs.MA2023

Multi-Agent Reinforcement Learning for Cooperative Air Transportation Services in City-Wide Autonomous Urban Air Mobility

Chanyoung Park, Gyu Seon Kim, Soohyun Park +2

The development of urban-air-mobility (UAM) is rapidly progressing with spurs, and the demand for efficient transportation management systems is a rising need due to the multifacet…

cs.MA2022

Multi-Agent Deep Reinforcement Learning for Efficient Passenger Delivery in Urban Air Mobility

Chanyoung Park, Soohyun Park, Gyu Seon Kim +3

It has been considered that urban air mobility (UAM), also known as drone-taxi or electrical vertical takeoff and landing (eVTOL), will play a key role in future transportation. By…